{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://www.jianshu.com/p/f4344669c694"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG:root:len of train_x : (3924, 64, 64, 3)\n",
      "DEBUG:root:train\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
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    {
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     "output_type": "stream",
     "text": [
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      "3916 0.6672081\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3917 1.2356837\n",
      "3918 0.9572546\n",
      "3919 1.5318867\n",
      "after 10 times run: accuracy is  0.7627421\n"
     ]
    },
    {
     "ename": "NameError",
     "evalue": "name 'validate' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-3-6d0badd4c9b1>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m     25\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     26\u001b[0m \u001b[0mmyconv\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtrain\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtrain_x\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtrain_y\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msavepath\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 27\u001b[1;33m \u001b[0mres\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mvalidate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtest_x\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0msavepath\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     28\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mres\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     29\u001b[0m \u001b[0mlog\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdebug\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'training is over, please run again'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'validate' is not defined"
     ]
    }
   ],
   "source": [
    "''' face detect\n",
    "other people's faces\n",
    "图片集下载:http://vis-www.cs.umass.edu/lfw/lfw.tgz\n",
    "'''\n",
    "# pylint: disable=invalid-name\n",
    "import os\n",
    "import logging as log\n",
    "import matplotlib.pyplot as plt\n",
    "import common\n",
    "import numpy as np\n",
    "from tensorflow.examples.tutorials.mnist import input_data\n",
    "import tensorflow as tf\n",
    "import cv2\n",
    "import tensorflow_face_conv as myconv\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "\n",
    "IMGSIZE = 64\n",
    "savepath = 'checkpoint/face.ckpt'\n",
    "Data = np.load('data.npy')\n",
    "Label = np.load('label.npy')\n",
    "train_x,test_x,train_y,test_y = train_test_split(Data,Label,test_size=0.2,random_state=42)\n",
    "train_x = train_x.astype(np.float32) / 255.0\n",
    "log.debug('len of train_x : %s', train_x.shape)\n",
    "\n",
    "myconv.train(train_x, train_y, savepath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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